Team:UC Davis

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<p class="centertext"><a href="https://2014.igem.org/Team:UC_Davis/Project_Overview">
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Project Overview</a>
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Welcome to the 2014 UC Davis iGEM team wiki!
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OliView: An Enzyme Based Electrochemical Biosensor Developed for Olive Oil Quality Control
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More than 65% of the extra virgin olive oil on shelves around the US is defective due to poor handling or deliberate adulteration with extraneous, non-beneficial oils. The most prevalent and identifying defect in olive oil is rancidity, indicating the absence of expected health benefits such as antioxidants and polyunsaturated fats. This summer, we are assembling a biosensor capable of quickly and cheaply evaluating rancidity defects in the chemical profile of olive oil, providing both consumers and retailers with a means of ensuring product quality.
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In a report conducted by the UC Davis Olive Oil Center, it was found that more than 65% of the extra virgin olive oil on shelves around the US is defective due to poor handling or deliberate adulteration with extraneous, non-beneficial oils. The most prevalent and identifying defect in olive oil is rancidity, indicating the absence of expected health benefits such as antioxidants and polyunsaturated fats. This summer, we engineered a biosensor capable of quickly and cheaply evaluating rancidity defects in the chemical profile of olive oil, providing both consumers and retailers with a means of ensuring product quality.<br><br>
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The project consisted of four components: Protein Engineering, Electrochemistry, Development of a user friendly potentiostat and signal processing. We were able to provide proof of concept for each component  of our device. With each component combined,  we had a fully functional electrochemical biosensor that could distinguish rancid olive oil from fresh. <br><br>
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<a href="https://static.igem.org/mediawiki/2014/0/07/UC_Davis_iGEM_2014_Practical_Implications_for_the_Development_and_Deployment_of_Engineered_Biosensors_in_Olive_Oil_Production.pdf" class="brightlink">Read full version of our practice and policy report</a><br>
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          <a href="https://2014.igem.org/Team:UC_Davis/Protein_Engineering">
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          <a href="https://2014.igem.org/Team:UC_Davis/Protein_Engineering"><h3>Protein Engineering</h3></a>
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          <p>Learn about how we engineered substrate specificity of Aldehyde Dehydrogenases and how we characterized specificity profiles.
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          <p>Take a look at how we developed a robust, coupleable electrochemical system to enable detection of various aldehydes in solution.         
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          <a href="https://2014.igem.org/Team:UC_Davis/Potentiostat_Design">
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          <h3>Signal Processing</h3>
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          <p>Take a look at the potentiostat and corresponding software we developed to acquire and process our data.
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          <h3>Results</h3>
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          <p>Here's the criteria that we met for this year's team.
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Latest revision as of 05:45, 24 November 2014

UC Davis iGEM 2014

Project Overview

OliView: An Enzyme Based Electrochemical Biosensor Developed for Olive Oil Quality Control

In a report conducted by the UC Davis Olive Oil Center, it was found that more than 65% of the extra virgin olive oil on shelves around the US is defective due to poor handling or deliberate adulteration with extraneous, non-beneficial oils. The most prevalent and identifying defect in olive oil is rancidity, indicating the absence of expected health benefits such as antioxidants and polyunsaturated fats. This summer, we engineered a biosensor capable of quickly and cheaply evaluating rancidity defects in the chemical profile of olive oil, providing both consumers and retailers with a means of ensuring product quality.

The project consisted of four components: Protein Engineering, Electrochemistry, Development of a user friendly potentiostat and signal processing. We were able to provide proof of concept for each component of our device. With each component combined, we had a fully functional electrochemical biosensor that could distinguish rancid olive oil from fresh.

Read full version of our practice and policy report

Retrieved from "http://2014.igem.org/Team:UC_Davis"